DocumentCode
1566473
Title
A Fast Nondominated Sorting Algorithm
Author
Shi, Chuan ; Chen, Ming ; Shi, Zhongzhi
Author_Institution
Inst. of Comput. Technol., Chinese Acad. of Sci., Beijing
Volume
3
fYear
2005
Firstpage
1605
Lastpage
1610
Abstract
The process of nondominated sorting is one of main time-consuming parts of multiobjective evolutionary algorithm (MOEA). Designing a fast nondominated sorting algorithm is crucial to improve the performance of MOEA. The paper uses a Better function to compare solutions, and theoretical analysis shows that the Better function has the properties of general symmetry and transitivity. Based on these properties, the Better nondominated sorting algorithm (BNS) is designed to reduce the comparisons among solutions distinctly. Through the simulation experiments and comparing study, the new algorithm is found to speed up the process of nondominated sorting in deed
Keywords
evolutionary computation; Better function; fast nondominated sorting algorithm; multiobjective evolutionary algorithm; multiobjective optimization problem; Algorithm design and analysis; Computers; Evolutionary computation; Laboratories; Pareto analysis; Pareto optimization; Sorting;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-9422-4
Type
conf
DOI
10.1109/ICNNB.2005.1614939
Filename
1614939
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